Ioannis Arapakis
Hideo Joho
Luis A. Leiva
Abstract
Payments in online ad auctions are typically derived from click-through rates, so that advertisers do not pay for ineffective ads. But advertisers often care about more than just clicks. That is, for example, if they aim to raise brand awareness or visibility. There is thus an opportunity to devise a more effective ad pricing paradigm, in which ads are paid only if they are actually noticed. This article contributes a novel auction format based on a pay-per-attention (PPA) scheme. We show that the PPA auction inherits the desirable properties (strategy-proofness and efficiency) as its pay-per-impression and pay-per-click counterparts, and that it also compares favourably in terms of revenues. To make the PPA format feasible, we also contribute a scalable diagnostic technology to predict user attention to ads in sponsored search using raw mouse cursor coordinates only, regardless of the page content and structure. We use the user attention predictions in numerical simulations to evaluate the PPA auction scheme. Our results show that, in relevant economic settings, the PPA revenues would be strictly higher than the existing auction payment schemes.
References
- Gagan Aggarwal, Ashish Goel, and Rajeev Motwani. 2006. Truthful auctions for pricing search keywords. In Proceedings of the EC.Google Scholar
Digital Library
- Ioannis Arapakis, Mounia Lalmas, B. Barla Cambazoglu, Mari-Carmen Marcos, and Joemon M. Jose. 2014. User engagement in online news: Under the scope of sentiment, interest, affect, and gaze. J. Assoc. Info. Sci. Technol. 65, 10 (2014).Google Scholar
- Ioannis Arapakis, Mounia Lalmas, and George Valkanas. 2014. Understanding within-content engagement through pattern analysis of mouse gestures. In Proceedings of the CIKM.Google ScholarDigital Library
- Ioannis Arapakis and Luis A. Leiva. 2016. Predicting user engagement with direct displays using mouse cursor information. In Proceedings of the SIGIR.Google Scholar
- Ioannis Arapakis, Luis A. Leiva, and B. Barla Cambazoglu. 2015. Know your onions: Understanding the user experience with the knowledge module in web search. In Proceedings of the CIKM.Google Scholar
- Ernesto Arroyo, Shawn Sullivan, and Ted Selker. 2006. CarCoach: A polite and effective driving coach. In Proceedings of the CHI EA.Google ScholarDigital Library
- Susan. Athey and Glenn Ellison. 2011. Position auctions with consumer search. Q. J. Econ. 126, 3 (2011).Google Scholar
- Susan Athey and Denis Nekipelov. 2014. A structural model of sponsored search advertising auctions. Mimeo (2014).Google Scholar
- Richard Atterer, Monika Wnuk, and Albrecht Schmidt. 2006. Knowing the user’s every move: User activity tracking for website usability evaluation and implicit interaction. In Proceedings of the WWW.Google ScholarDigital Library
- Lawrence M. Ausubel and Oleg Baranov. 2019. Core-selecting auctions with incomplete information. International Journal of Game Theory. https://doi.org/10.1007/s00182-019-00691-3Google Scholar
- Yoram Bachrach. 2010. Honor among thieves: Collusion in multi-unit auctions. Proceedings of the AAMAS (2010).Google Scholar
- Yoram Bachrach, Sofia Ceppi, Ian A. Kash, Peter Key, and David Kurokawa. 2014. Optimising trade-offs among stakeholders in ad auctions. In Proceedings of the EC.Google ScholarDigital Library
- Nicola Barbieri, Fabrizio Silvestri, and Mounia Lalmas. 2016. Improving post-click user engagement on native ads via survival analysis. In Proceedings of the WWW.Google ScholarDigital Library
- Oswald Barral, Ilkka Kosunen, Tuukka Ruotsalo, Michiel M. Spapé, Manuel J. Eugster, Niklas Ravaja, Samuel Kaski, and Giulio Jacucci. 2016. Extracting relevance and affect information from physiological text annotation. User Model. User-Adap. 26, 5 (2016).Google Scholar
- Thomas Blake, Chris Nosko, and Steven Tadelis. 2015. Consumer heterogeneity and paid search effectiveness: A large-scale field experiment. Econometrica 83, 1 (2015).Google Scholar
- Michael Bohan and Alex Chaparro. 1998. Age-related differences in performance using a mouse and trackball. Hum. Factors 42, 2 (1998).Google Scholar
- Tilman Borgers, Ingemar Cox, Martin Pesendorfer, and Vaclav Petricek. 2013. Equilibrium bids in sponsored search auctions: Theory and evidence. Amer. Econ. J.: Microeconomics 5, 4 (2013).Google ScholarCross Ref
- Brightfish, Profacts, and Lumen. 2018. From viewable to viewed: Using eye tracking to understand the reality of attention to advertising across media. White paper. Retrieved from https://effectiveviews.be/files/White_Paper_From_Viewable_to_viewed.pdf.Google Scholar
- Y. Chen, Y. Liu, M. Zhang, and S. Ma. 2017. User satisfaction prediction with mouse movement information in heterogeneous search environment. IEEE Trans. Knowl. Data. Eng. 29, 11 (2017).Google ScholarCross Ref
- Hana Choi, Carl F. Mela, Santiago Balseiro, and Adam Leary. 2018. Online display advertising markets: A literature review and future directions. Columbia Business School Research Paper No. 18-1.Google Scholar
- Edward H. Clarke. 1971. Multipart pricing of public goods. Public Choice 11 (1971).Google Scholar
- Mark Claypool, Phong Le, Makoto Wased, and David Brown. 2001. Implicit interest indicators. In Proceedings of the IUI.Google ScholarDigital Library
- Francesco Decarolis, Maris Goldmanis, and Antonio Penta. 2018. Marketing agencies and collusive bidding in online ad auctions. Management Science (forthcoming).Google Scholar
- Fernando Diaz, Ryen White, Georg Buscher, and Dan Liebling. 2013. Robust models of mouse movement on dynamic web search results pages. In Proceedings of the CIKM.Google ScholarDigital Library
- Abdigani Diriye, Ryen White, Georg Buscher, and Susan Dumais. 2012. Leaving so soon?: Understanding and predicting web search abandonment rationales. In Proceedings of the CIKM.Google ScholarDigital Library
- Benjamin Edelman, Michael Ostrovsky, and Michael Schwarz. 2007. Internet advertising and the generalized second-price auction: Selling billions of dollars worth of keywords. Amer. Econ. Rev. 97, 1 (2007).Google ScholarCross Ref
- Benjamin Edelman and Michael Schwarz. 2010. Optimal auction design and equilibrium selection in sponsored search auctions. Amer. Econ. Rev. 100, 2 (2010).Google ScholarCross Ref
- Henry A. Feild, James Allan, and Rosie Jones. 2010. Predicting searcher frustration. In Proceedings of the SIGIR.Google ScholarDigital Library
- Kenneth Fjell. 2009. Online advertising: Pay-per-view versus pay-per-click—A comment. Int. J. Res. Market. 8, 2--3 (2009).Google Scholar
- Kristin Fridgeirsdottir and Sami Najafi-Asadolahi. 2018. Cost-per-impression pricing for display advertising. Oper. Res. 66, 3 (2018).Google Scholar
- Joseph H. Goldberg, Mark J. Stimson, Marion Lewenstein, Neil Scott, and Anna M. Wichansky. 2002. Eye tracking in web search tasks: Design implications. In Proceedings of the ETRA.Google Scholar
- Renato Gomes and Kane Sweeney. 2014. Bayes–Nash equilibria of the generalized second-price auction. Games Econ. Behav. 86 (2014).Google Scholar
- Google. 2014. The Importance of Being Seen: Viewability Insights for Digital Marketers and Publishers. Technical Report.Google Scholar
- Theodore Groves. 1973. Incentives in teams. Econometrica 41, 4 (1973).Google Scholar
- Max Grusky, Jeiran Jahani, Josh Schwartz, Dan Valente, Yoav Artzi, and Mor Naaman. 2017. Modeling sub-document attention using viewport time. In Proceedings of the CHI.Google ScholarDigital Library
- Qi Guo and Eugene Agichtein. 2008. Exploring mouse movements for inferring query intent. In Proceedings of the SIGIR.Google ScholarDigital Library
- Qi Guo and Eugene Agichtein. 2010. Ready to buy or just browsing?: Detecting web searcher goals from interaction data. In Proceedings of the SIGIR.Google ScholarDigital Library
- Qi Guo and Eugene Agichtein. 2012. Beyond dwell time: Estimating document relevance from cursor movements and other post-click searcher behavior. In Proceedings of the WWW.Google ScholarDigital Library
- Qi Guo, Haojian Jin, Dmitry Lagun, Shuai Yuan, and Eugene Agichtein. 2013. Mining touch interaction data on mobile devices to predict web search result relevance. In Proceedings of the SIGIR.Google ScholarDigital Library
- Qi Guo, Dmitry Lagun, and Eugene Agichtein. 2012. Predicting web search success with fine-grained interaction data. In Proceedings of the CIKM.Google ScholarDigital Library
- Ken Hendricks, Robert Porter, and Guofu Tan. 2008. Bidding rings and the winner’s curse. RAND J. Econ. 39, 4 (2008).Google ScholarCross Ref
- Shang H. Hsu, Chien Chung Huang, Yang Hui Tsuang, and Jui Sheng Sun. 1999. Effects of age and gender on remote pointing performance and their design implications. Int. J. Ind. Ergon. 23, 5 (1999).Google ScholarCross Ref
- Jian Hu, Hua-Jun Zeng, Hua Li, Cheng Niu, and Zheng Chen. 2007. Demographic prediction based on user’s browsing behavior. In Proceedings of the WWW.Google ScholarDigital Library
- Jeff Huang, Ryen White, and Georg Buscher. 2012. User see, user point: Gaze and cursor alignment in web search. In Proceedings of the CHI.Google ScholarDigital Library
- Jeff Huang, Ryen W. White, Georg Buscher, and Kuansan Wang. 2012. Improving searcher models using mouse cursor activity. In Proceedings of the SIGIR.Google ScholarDigital Library
- Jeff Huang, Ryen W. White, and Susan Dumais. 2011. No clicks, no problem: Using cursor movements to understand and improve search. In Proceedings of the CHI.Google ScholarDigital Library
- Sharethrough IPG. 2013. Native Ads vs Banner Ads: Native Ad Research from IPG 8 Sharethrough Reveals that In-Feed Beats Banners. Technical Report.Google Scholar
- Giulio Jacucci, Oswald Barral, Pedram Daee, Markus Wenzel, Baris Serim, Tuukka Ruotsalo, Patrik Pluchino, Jonathan Freeman, Luciano Gamberini, Samuel Kaski, and Benjamin Blankertz. 2019. Integrating neurophysiologic relevance feedback in intent modeling for information retrieval. J. Assoc. Info. Sci. Technol. 70, 9 (2019).Google Scholar
- Tiffany Jastrzembski, Neil Charness, Patricia Holley, and Jeffrey Feddon. 2003. Input devices for web browsing: Age and hand effects. Universal Access Info. 4 (2003).Google Scholar
- Philippe Jehiel and Laurent Lamy. 2015. On discrimination in auctions with endogenous entry. Amer. Econ. Rev. 105 (2015).Google Scholar
- Zilong Jiang, Shu Gao, and Wei Dai. 2016. Research on CTR prediction for contextual advertising based on deep architecture model. Control Eng. Appl. Info. 18 (2016).Google Scholar
- S.M. Johnson, P. Smith, and S. Tucker. 1982. Response format of the job descriptive index: Assessment of reliability and validity by the multitrait-multimethod matrix. J. Appl. Psychol. 67, 4 (1982).Google ScholarCross Ref
- Alexander Kolesnikov, Yury Logachev, and Valeriy Topinskiy. 2012. Predicting CTR of new ads via click prediction. In Proceedings of the CIKM.Google ScholarDigital Library
- Dmitry Lagun, Mikhail Ageev, Qi Guo, and Eugene Agichtein. 2014. Discovering common motifs in cursor movement data for improving web search. In Proceedings of the WSDM.Google ScholarDigital Library
- Dmitry Lagun and Eugene Agichtein. 2015. Inferring searcher attention by jointly modeling user interactions and content salience. In Proceedings of the SIGIR.Google ScholarDigital Library
- Dmitry Lagun, Chih-Hung Hsieh, Dale Webster, and Vidhya Navalpakkam. 2014. Toward better measurement of attention and satisfaction in mobile search. In Proceedings of the SIGIR.Google ScholarDigital Library
- Dmitry Lagun, Donal McMahon, and Vidhya Navalpakkam. 2016. Understanding mobile searcher attention with rich ad formats. In Proceedings of the CIKM.Google ScholarDigital Library
- Preston Lahaie and Sébastien McAfee. 2011. Efficient ranking in sponsored search auctions. In Proceedings of the WINE.Google Scholar
- Luis A. Leiva. 2011. Restyling website design via touch-based interactions. In Proceedings of the MobileHCI.Google ScholarDigital Library
- Luis A. Leiva and Jeff Huang. 2015. Building a better mousetrap: Compressing mouse cursor activity for web analytics. Info. Process. Manag. 51, 2 (2015).Google Scholar
- Luis A. Leiva and Roberto Vivó. 2013. Web browsing behavior analysis and interactive hypervideo. ACM Trans. Web 7, 4 (2013).Google ScholarDigital Library
- Yixuan Li, Pingmei Xu, Dmitry Lagun, and Vidhya Navalpakkam. 2017. Toward measuring and inferring user interest from gaze. In Proceedings of the WWW Companion.Google ScholarDigital Library
- Tomas Lindberg, Risto Näsänen, and Kiti Müller. 2006. How age affects the speed of perception of computer icons. Displays 27, 4 (2006).Google Scholar
- Yiqun Liu, Ye Chen, Jinhui Tang, Jiashen Sun, Min Zhang, Shaoping Ma, and Xuan Zhu. 2015. Different users, different opinions: Predicting search satisfaction with mouse movement information. In Proceedings of the SIGIR.Google ScholarDigital Library
- Yiqun Liu, Chao Wang, Ke Zhou, Jianyun Nie, Min Zhang, and Shaoping Ma. 2014. From skimming to reading: A two-stage examination model for web search. In Proceedings of the CIKM.Google ScholarDigital Library
- George J Mailath and Peter Zemsky. 1991. Collusion in second price auctions with heterogeneous bidders. Games Econ. Behav. 3, 4 (1991).Google Scholar
- Andrea Mangani. 2004. Online advertising: Pay-per-view versus pay-per-click. Int. J. Res. Market. 2, 4 (2004).Google Scholar
- Yishay Mansour, S. Muthukrishnan, and Noam Nisan. 2012. Doubleclick ad exchange auction. CoRR abs/1204.0535 (2012).Google Scholar
- Jiaxin Mao, Yiqun Liu, Noriko Kando, Zexue He, Min Zhang, and Shaoping Ma. 2018. A two-stage model for user’s examination behavior in mobile search. In Proceedings of the CHIIR.Google ScholarDigital Library
- Jiaxin Mao, Cheng Luo, Min Zhang, and Shaoping Ma. 2018. Constructing click models for mobile search. In Proceedings of the SIGIR.Google ScholarDigital Library
- Mari-Carmen Marcos, Ferran Gavin, and Ioannis Arapakis. 2015. Effect of snippets on user experience in web search. In Proceedings of the INTERACCION.Google ScholarDigital Library
- Daniel Martín-Albo, Luis A. Leiva, Jeff Huang, and Réjean Plamondon. 2016. Strokes of insight: User intent detection and kinematic compression of mouse cursor trails. Info. Process. Manag. 52, 6 (2016).Google Scholar
- Winter Mason and Siddharth Suri. 2012. Conducting behavioral research on Amazon’s Mechanical Turk. Behav. Res. Methods 44, 1 (2012).Google Scholar
- Randolph McAfee and John McMillan. 1992. Bidding rings. Amer. Econ. Rev. 82, 3 (1992).Google Scholar
- L. McCay-Peet, M. Lalmas, and V. Navalpakkam. 2012. On saliency, affect and focused attention. In Proceedings of the CHI.Google Scholar
- Paul Milgrom and Joshua Mollner. 2018. Equilibrium selection in auctions and high stakes games. Econometrica 86, 1 (2018).Google Scholar
- Roger B. Myerson. 1981. Optimal auction design. Math. Oper. Res. 6, 1 (1981).Google Scholar
- Sami Najafi-Asadolahi and Kristin Fridgeirsdottir. 2014. Cost-per-click pricing for display advertising. Manuf. Serv. Oper. Manage. 16, 4 (2014).Google Scholar
- Abhirup Nath, Shibnath Mukherjee, Prateek Jain, Navin Goyal, and Srivatsan Laxman. 2013. Ad impression forecasting for sponsored search. In Proceedings of the WWW.Google ScholarDigital Library
- Vidhya Navalpakkam, LaDawn Jentzsch, Rory Sayres, Sujith Ravi, Amr Ahmed, and Alex Smola. 2013. Measurement and modeling of eye-mouse behavior in the presence of nonlinear page layouts. In Proceedings of the WWWW.Google ScholarDigital Library
- Michael Ostrovsky and Michael Schwarz. 2011. Reserve prices in internet advertising auctions: A field experiment. In Proceedings of the EC.Google ScholarDigital Library
- Justin W. Owens, Barbara S. Chaparro, and Evan M. Palmer. 2011. Text advertising blindness: The new banner blindness?J. Usabil. Stud. 6, 3 (2011).Google Scholar
- Renato Paes Leme and Éva Tardos. 2010. Pure and Bayes–Nash price of anarchy for generalized second price auction. In Proceedings of the FOCS.Google Scholar
- Avar Pentel. 2017. Predicting age and gender by keystroke dynamics and mouse patterns. In Proceedings of the Adj. UMAP.Google ScholarDigital Library
- Ben Roberts, Dinan Gunawardena, Ian A. Kash, and Peter Key. 2016. Ranking and tradeoffs in sponsored search auctions. ACM Trans. Econ. Comput. 4, 3 (2016).Google ScholarDigital Library
- R. Rosenholtz, Y. Li, J. Mansfield, and Z. Jin. 2005. Feature congestion: A measure of display clutter. In Proceedings of the CHI.Google Scholar
- Bracha Shapira, Meirav Taieb-Maimon, and Anny Moskowitz. 2006. Study of the usefulness of known and new implicit indicators and their optimal combination for accurate inference of users interests. In Proceedings of the SAC.Google ScholarDigital Library
- Michael W. Smith, Joseph Sharit, and Sara J. Czaja. 1999. Aging, motor control, and the performance of computer mouse tasks. Hum. Factors 41, 3 (1999).Google Scholar
- Maximilian Speicher, Andreas Both, and Martin Gaedke. 2013. TellMyRelevance!: Predicting the relevance of web search results from cursor interactions. In Proceedings of the CIKM.Google Scholar
- David R.M. Thompson and Kevin Leyton-Brown. 2013. Revenue optimization in the generalized second-price auction. In Proceedings of the EC.Google Scholar
- Hal R. Varian. 2007. Position auctions. Int. J. Ind. Organ. 25, 6 (2007).Google ScholarCross Ref
- Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N. Gomez, Lukasz Kaiser, and Illia Polosukhin. 2017. Attention is all you need. In Proceedings of the NIPS.Google Scholar
- William Vickrey. 1961. Counterspeculation, auctions, and competitive sealed tenders. J. Finance 16, 1 (1961).Google ScholarCross Ref
- Neff Walker, David A. Philbin, and Arthur D. Fisk. 1997. Age-related differences in movement control: Adjusting submovement structure to optimize performance. J. Gerontol. A Biol. Sci. Med. Sci. 52, 1 (1997).Google Scholar
- Xiaochuan Wang, Ning Su, Zexue He, Yiqun Liu, and Shaoping Ma. 2018. A large-scale study of mobile search examination behavior. In Proceedings of the SIGIR.Google ScholarDigital Library
- T. Yamauchi and C. Bowman. 2014. Mining cursor motions to find the gender, experience, and feelings of computer users. In Proceedings of the ICDM.Google Scholar
- Shuangfei Zhai, Keng-hao Chang, Ruofei Zhang, and Zhongfei Mark Zhang. 2016. DeepIntent: Learning attentions for online advertising with recurrent neural networks. In Proceedings of the KDD.Google ScholarDigital Library
Index Terms
A Price-per-attention Auction Scheme Using Mouse Cursor Information
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